In modern systems, the processing takes place in distributed fashion, so that the relevant data records need to be transmitted via a network to a receiver node on which the calculation steps are executed. This may also involve mobile nodes. Preferably, processing takes place in the cloud (headword: cloud computing). An essential aspect in this case is the available network bandwidth.
Medical data objects (e.g. image data and medical findings reports) contain a wealth of information that is relevant to protection (particularly protected health information, PHI data records for short) and that is meant to be accessible only to a specific group of recipients and not publicly, since these data can be used to identify the patient and other persons (such as doctors or relatives). For certain purposes, e.g. transmission of the data via a publicly accessible network, e.g. for the remote maintenance of appliances, it is therefore necessary to remove selected information from the data record in order to pseudonymize the data objects. This preparation of the data is demanded by security regulations.
To date, the data objects have been pseudonymized on the basis of predefined, fixed profiles that define what information needs to be removed from the data objects. This occurs uniformly and to a certain extent statically, since the edit context and purpose of subsequent data processing are not taken into account for the pseudonymization.
It is therefore important to perform necessary preprocessing steps (and also pseudonymization of the data records to be transmitted) such that it is possible to be flexible regarding the required transmission speed or the network bandwidth in order to be able to react dynamically and adaptively to technical transmission parameters for the data transmission of the network. If there is only a low network transmission capacity available, for example, it needs to be possible to calculate the preprocessing steps and particularly the pseudonymization using a variable computation specification such that in this case a higher degree of pseudonymization and hence a smaller volume of data needs to be transmitted. This solves the specific technical problem of adaptively allowing for the available network capacity during the pseudonymization and reducing the volume of data as far as possible depending on the applications.
It also needs to be possible to be able to execute the pseudonymization calculation on the basis of planned processing of the data on a receiver node. The reason is that it is relevant to pseudonymization whether the data to be transmitted are intended to be used to execute remote appraisal or whether the data are intended to be used for a clinical study (in which case, in contrast to the first application, the statement about the examination protocol used on the respective modality would be important; these data should then not be lost during pseudonymization and should be transmitted as well), for example.